2013/12/31 by S. E. Clark, S E Clark, J. E. G. Peek +3 · 6 citations
Physics and Astronomy · #Astronomy and Astrophysical Research #Astrophysics and Star Formation Studies #Field (mathematics) #Galactic plane #Galaxies: Formation, Evolution, Phenomena #Hough transform #Interstellar medium #Magnetic field #Measure (data warehouse) #Plane (geometry) #Starlight #astro-ph.GA
paper · pdf · doi:10.1088/0004-637x/789/1/82
published as M.E. 2014, ApJ, 789, 82 · 13 pages, 13 figures. Accepted to the Astrophysical Journal
arxiv created 2014/05/23 · openalex publication_date 2014/06/17 · arxiv updated 2014/06/19 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06
We present observations of a new group of structures in the diffuse Galactic interstellar medium (ISM): slender, linear H i features we dub "fibers" that extend for many degrees at high Galactic latitude. To characterize and measure the extent and strength of these fibers, we present the Rolling Hough Transform, a new machine vision method for parameterizing the coherent linearity of structures in the image plane. With this powerful new tool we show that the fibers are oriented along the interstellar magnetic field as probed by starlight polarization. We find that these low column density ( cm −2 ) fiber features are most likely a component of the local cavity wall, about 100 pc away. The H i data we use to demonstrate this alignment at high latitude are from the Galactic Arecibo L-Band Feed Array H i (GALFA-H i ) Survey and the Parkes Galactic All Sky Survey. We find better alignment in the higher resolution GALFA-H i data, where the fibers are more visually evident. This trend continues in our investigation of magnetically aligned linear features in the Riegel–Crutcher H i cold cloud, detected in the Southern Galactic Plane Survey. We propose an application of the RHT for estimating the field strength in such a cloud, based on the Chandrasekhar–Fermi method. We conclude that data-driven, quantitative studies of ISM morphology can be very powerful predictors of underlying physical quantities.